Humanoid Robot Training Data: How Much Do You Actually Need?
How much humanoid robot training data do you actually need? The honest answer depends on three things: your deployment tier, your model architecture, and what “enough” means for your specific use case. The humanoid robot training data question every team asks differently Ask five humanoid robotics teams how much training data they need and you […]
How to Scale Teleop Data Collection Without Losing Quality
Scaling teleop data collection is one of the hardest operational problems in robotics. The volume grows quickly. The quality does not always follow. The teleop data collection quality cliff nobody warns you about Scaling teleoperation data collection sounds straightforward: hire more operators, run more sessions, collect more trajectories. In practice, most teams hit a quality […]
What enterprise procurement actually asks about robotics data
When a robotics startup moves from Series A to Series B and starts selling enterprise, the data partner conversation changes. Seven questions procurement actually asks — in order of frequency.
Lessons from 50,000 humanoid trajectories
Five things we learned getting from zero to 50K trajectories across Figure, Optimus, and Apollo. Operator pacing matters more than skill, failure-recovery data is what actually moves production performance, and annotation cost is the dominant cost — not capture.
Why we built Roborax as a standalone brand
When we first started talking to humanoid robotics teams, three out of four would ask: “You’re inside a $200M BPO — what do you know about robotics data?” Here’s why we chose to spin out the brand while keeping the operational spine.